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Future Finance

Future Finance

Glenn Hopper & Paul Barnhurst

Future Finance is a podcast that delves into the transformative world of finance hosted by Paul Barnhurst, aka The FP&A Guy, and Glenn Hopper, emphasizing the impact of technology and artificial intelligence within the finance profession. Each episode brings listeners the latest news on AI and financial technology, insightful discussions, expert analyses, and forward-thinking ideas, exploring how AI and technological innovations are reshaping corporate finance as we know it. The podcast will become a must-listen for anyone interested in the evolving intersection of technology and finance

113 - AI, Decision Culture, and the Future of Enterprise Finance with Matija Nakic
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  • 113 - AI, Decision Culture, and the Future of Enterprise Finance with Matija Nakic

    In this episode of Future Finance, hosts Glenn Hopper and Paul Barnhurst sit down with Matija Nakic, CEO and Co-founder of Farseer, to discuss how AI is changing financial planning, enterprise software, and decision-making. Matija shares why asking better questions matters, how finance teams can build stronger AI workflows, and where Excel still fits in modern planning.

    Matija Nakic is the CEO and Co-founder of Farseer, an AI-native SaaS platform for business modeling, planning, and analysis. With a background in computer engineering, an MBA, and experience across B2B enterprise software, she has progressed from developer to product director and now leads Farseer’s mission to improve how financial professionals plan, model, and make decisions.

    In this episode, you will discover:

    Why asking the right questions matters with AI.How finance can build a stronger decision culture.Why clean data and governance still matter.How AI can speed up planning and forecasting.When to use Excel versus planning software.

    AI can dramatically accelerate finance work, but speed alone does not create better decisions. Matija explains that effective AI adoption still depends on fundamentals such as clean data, consistent definitions, connected data sources, business logic, and human judgment

    Follow Matija:

    LinkedIn: https://hr.linkedin.com/in/matija-nakic

    Company: https://www.farseer.com/

    Follow Glenn:

    LinkedIn: https://www.linkedin.com/in/gbhopperiii

    Follow Paul:

    LinkedIn: https://www.linkedin.com/in/thefpandaguy

    Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.

    Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.

    Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.

    In Today’s Episode:

    [00:00] - Trailer

    [05:22] - Why Farseer Was Built

    [08:35] - AI and the Future of Enterprise Software

    [13:30] - Building Faster with AI

    [17:24] - Why Asking the Right Questions Matters

    [22:55] - The Three Levels of AI Adoption

    [24:57] - Building a Decision Culture

    [32:04] - When Excel Is Still the Right Tool

    [35:57] - Governance, Context & Audit Trails

    [36:37] - Rapid-Fire Questions

    [39:21] - Turning Frustration with Planning Into Farseer

    [40:59] - Closing Thoughts

    Wed, 23 Sep 2026 - 41min
  • 112 - Why CFOs Should Lead AI Adoption Instead of Leaving It Solely to IT

    In this episode of Future Finance, Paul Barnhurst speaks with Glenn Hopper about his new book, The AI-Ready CFO, and what finance leaders need to do to successfully adopt AI. Glenn explains why CFOs must take a leadership role in AI strategy, how finance can balance innovation with risk management, and why successful AI implementation starts with data readiness, process improvement, and strong governance.

    In this episode, you will discover:

    Why CFOs should lead AI adoption.How finance can balance AI, speed, and risk.Why data readiness is essential before AI implementation.How to build trust through governance and transparency.How to create effective AI pilots and scale success.

    Glenn explains that AI adoption is not just about choosing new tools. Finance leaders need to understand their current processes, establish a baseline, identify opportunities, run focused pilots, and use evidence to decide what should be scaled.

    Follow Glenn:

    LinkedIn: https://www.linkedin.com/in/gbhopperiii

    Glenn’s new book: The AI-Ready CFO

    https://robocfo.ai/ai-ready-cfo

    Follow Paul:

    LinkedIn: https://www.linkedin.com/in/thefpandaguy

    Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.

    Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.

    Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.

    In Today’s Episode:

    [00:00] - Trailer: The AI-Ready CFO

    [03:54] - The AI-Ready CFO Explained

    [08:59] - The Changing CFO Role

    [13:27] - Why Finance Should Lead AI

    [16:46] - AI Change Management

    [21:32] - Building an AI Strategy

    [27:39] - Trust, Governance & AI

    [32:32] - Transparent AI Processes

    [36:30] - AI Build vs. Buy

    [40:02] - Building AI Agents

    [43:21] - Closing Thoughts

    Wed, 16 Sep 2026 - 18min
  • 111 - The CFO Should Own AI, Not IT | Glenn Hopper on The AI-Ready CFO

    In this episode of Future Finance, Paul Barnhurst speaks with Glenn Hopper about his new book, The AI-Ready CFO, and how finance leaders can successfully navigate AI adoption. Glenn explains why CFOs need to take ownership of AI strategy, how to balance speed with risk, and why strong governance, data readiness, and change management are essential for building trust in AI.

    In this episode, you will discover:

    Why CFOs need to play a leading role in AI adoption.How finance teams can balance AI speed with governance and risk management.Why data readiness and process documentation are critical before implementing AI.How to build trust in AI through transparency, audit trails, and human oversight.How CFOs can create effective AI pilot programs and scale successful initiatives.

    AI adoption is not just about selecting new tools. Glenn explains that successful implementation starts with understanding current processes, improving data readiness, creating measurable baselines, and building systems that allow people to trust AI outputs. For CFOs, the future role is not becoming an AI engineer, but becoming the leader who ensures AI is used responsibly and effectively across the organization.

    Follow Glenn:

    LinkedIn: https://www.linkedin.com/in/gbhopperiii

    Glenn’s new book: The AI-Ready CFO

    https://robocfo.ai/ai-ready-cfo

    Follow Paul:

    LinkedIn: https://www.linkedin.com/in/thefpandaguy

    Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.

    Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.

    Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.

    In Today’s Episode:

    [00:00] - Trailer: The AI-Ready CFO

    [03:54] - The AI-Ready CFO Explained

    [08:59] - The Changing CFO Role

    [13:27] - Why Finance Should Lead AI

    [16:46] - AI Change Management

    [21:32] - Building an AI Strategy

    [27:39] - Trust, Governance & AI

    [32:32] - Transparent AI Processes

    [36:30] - AI Build vs. Buy

    [40:02] - Building AI Agents

    [43:21] - Closing Thoughts

    Wed, 09 Sep 2026 - 46min
  • 110 - Why Better Workflows Matter More Than Better Prompts

    In this episode of Future Finance, Paul Barnhurst and Glenn Hopper discuss AI fatigue and why finance professionals should focus less on chasing new models and more on using AI effectively. They share practical ways to improve AI results through better instructions, reference files, context, and data foundations.

    In this episode, you will discover:

    Why AI fatigue is becoming a real challenge.Why prompting alone is no longer enough.How context and reference files improve AI results.Why clean data and clear KPIs matter.How finance teams can start using AI more effectively.

    Paul and Glenn emphasize that finance teams do not need to build complicated systems immediately. Starting with clear data definitions, documented sources, and simple context files can already make AI much more useful.

    Follow Glenn:

    LinkedIn: https://www.linkedin.com/in/gbhopperiii

    Follow Paul:

    LinkedIn: https://www.linkedin.com/in/thefpandaguy

    Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.

    Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.

    Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.

    In Today's Episode:

    [00:00] - Introduction

    [01:07] - AI Fatigue

    [04:09] - Using AI Effectively

    [05:44] - The Changing Role of Prompting

    [07:40] - AI for Financial Modelling

    [11:37] - AI and Finance Data

    [14:47] - Building a Data Foundation

    [18:10] - Practical AI Tips

    [19:08] - Closing Thoughts

    Wed, 02 Sep 2026 - 19min
  • 109 - How Finance Pros Should Manage Data Context and Token Forecasting

    In this episode of Future Finance, hosts Paul Barnhurst and Glenn Hopper discuss AI fatigue, better ways for finance teams to use AI, and the growing challenge of forecasting AI costs. They explore why finance leaders should focus less on chasing new models and more on building the data, context, and workflows needed to get real value from AI.

    In this episode, you will discover:

    Why finance teams should stop chasing every new AI model.Why context is becoming more important than prompting alone.How better KPIs and data foundations improve AI results.How organizations can forecast and manage AI token costs.Why AI success should be measured by business outcomes.

    Paul and Glenn explain why effective AI adoption isn't about using the most tokens or knowing every new tool. It's about using AI to help finance make better, faster decisions.

    Follow Glenn:

    LinkedIn: https://www.linkedin.com/in/gbhopperiii

    Follow Paul:

    LinkedIn: https://www.linkedin.com/in/thefpandaguy

    Disclosure: Portions of this episode (such as the introduction or promotional segments) use AI-generated voice narration produced under human editorial review.

    Future Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai.

    Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.

    In Today’s Episode:

    [00:00] – Trailer

    [03:17] – AI Fatigue & Model Overload

    [09:38] – Beyond Prompt Engineering

    [16:03] – Building Better AI Context

    [24:29] – Organizing Finance Knowledge

    [27:29] – Token Maxing & AI Costs

    [32:06] – Forecasting Token Spend

    [38:23] – Focusing on Business Value

    [41:43] – Closing Thoughts

    Wed, 26 Aug 2026 - 42min
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